LoadImpact’s post explains how you do this, and it’s a very useful article – I think it deserves to be shared around some more. It basically takes your per-hour data and timespends, and estimates the average concurrent visitor numbers from that.

But while I was testing this out, 2 things occurred to me –One – is it misleading? when you calculate a peak, you’re taking an average over an hour. The actual spike would be far higher at the point of occurrence – i.e. if your average concurrent users are 10, and you calculate a peak of, say, 50 on one day – the logical assumption is that there will be fifty people on the site together, assuming a timespend of a minute. But those 3000 people could have come 1500 together in the first minute and 25 every minute after – so the actual peak would be 1500, something that doesn’t show or get implied.(Maybe that’s why it’s not an official feature?)

Two – Now, Google is recording a timestamp on each open. They can calculate minute-to-minute, even second-to-second usage. This is fairly important data – Google, why don’t you just add it to the layout of the basic dashboard anyway? Annual average and peak within the selected daterange would be fine.

Moral of the story – if you’re using this method for an approximation, go ahead. But it might be a little misleading on the extremely high values and also on a series of similar, seemingly identical values. Remember that pinch of salt.